Citations

Aims Routine application of PD-L1 immunohistochemistry (IHC) in colorectal cancer (CRC) is limited due to lack of standardized scoring criteria, antibody clones, and intratumoral staining heterogeneity. We assessed PD-L1 protein expression on full face CRC tissue sections and applied two algorithms based on the published clinical trials that support the recent FDA approval for immune checkpoint inhibitors (ICPI) therapy in non-small cell lung cancer (NSCLC). Methods PD-L1/CD274 IHC (Roche/Ventana, clone SP142) was performed on representative tumour blocks from 52 mismatch repair-deficient (MMR-D) and 52 MMR-proficient (MMR-P) CRCs. Membranous PD-L1 expression was scored for the tumour cell (TC) and tumour-infiltrating immune cell (IC) components. PD-L1 positivity status was determined based on the published NSCLC clinical trials that utilized the Ventana SP142 assay. Hybrid capture-based comprehensive genomic profiling (CGP) was performed on a separate set of 2268 clinically advanced CRCs and the frequency of PD-L1/PD-L2 amplification was determined. Results PD-L1 expression in the TC and IC correlated with MMR-D (p=0.013, p<0.0001), T stage (p=0.036, p=0.0036) and clinical stage (p=0.022, p=0.0037). PD-L1 positivity status correlated with MMR-D by two algorithms. Five of 2268 (<1%) advansced CRCs demonstrated amplification of either the PD-L1 or PD-L2 genes by CGP. Conclusions PD-L1 expression in TC and IC is associated with advanced stage and MMR-D. PD-L1 positivity status by the published algorithm is associated with MMR-D. PD-L1 amplification is extremely uncommon in CRC. Evaluation of whole tissue section and incorporation of IC staining enhance the sensitivity to screen patients who may benefit from ICPI therapy.

AbstractQuantitative measurement of β‐amyloid from amyloid PET scans typically relies on localizing target and reference regions by image registration to MRI. In this work, we present a series of simulations where 50 small random perturbations of starting location and orientation were applied to each subject's PET scan, and rigid registration usingspm_coregwas performed between each perturbed PET scan and its corresponding MRI. We then measured variation in the output PET‐MRI registrations and how this variation affected the resulting SUVR measurements. We performed these experiments using scans of 1196 participants, half using 18F florbetapir and half using 11C PiB. From these experiments, we measured the magnitude of the imprecision in the rigid registration steps used to localize measurement regions, and how this contributes to the overall imprecision in SUVR measurements. Unexpectedly, we found for both tracers that the imprecision in these measurements depends on the degree of amyloid tracer uptake, and thus also indirectly on Alzheimer's disease clinical status. We then examined common choices of reference regions, and we show that SUVR measurements using supratentorial white matter references are relatively resistant to this source of error. We also show that the use of partial volume correction further magnifies the effects of registration imprecision on SUVR measurements. Together, these results suggest that this rigid registration step is an attractive target for future work in improving measurement techniques.Hum Brain Mapp 38:3323–3336, 2017. ©2017 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.